以数据为桥梁，将商业洞察转化为决策行动。 Bridging commercial intuition with data-driven execution.
我是一名管理科学与工程专业的商业数据分析实验班学生，致力于通过数据驱动的深度洞察，弥合学术严谨性与商业执行力之间的鸿沟。
在过往的科研实践中，我始终保持极高的求知欲与探索动力，善于将复杂的行业痛点转化为可量化的分析框架。我执行“以数据为决策基石”的工作方式，能够熟练运用统计建模、机器学习及另类数据挖掘工具，辅助决策过程。
我深信“低 Ego，高执行”的职业哲学：在团队中，我追求信息的客观性而非个人的观点验证，专注于以最小的阻力推动项目进度，确保分析结论具备落地的韧性。作为一名自驱力极强的行动者，我习惯于在面对非结构化信息时，主动构建流程与工具，将问题定义清楚并高效闭环。我不仅关注数据的表面逻辑，更致力于发现数据背后的商业叙事。
I am a Business Data Analysis undergraduate, dedicated to bridging the gap between academic rigor and commercial execution through data-driven insights.
Driven by a persistent intellectual curiosity, I excel at deconstructing complex industry pain points into actionable, quantitative frameworks. My analytical approach is fundamentally data-centric, leveraging statistical modeling, machine learning, and alternative data mining to provide a robust foundation for strategic decision-making.
I subscribe to a professional philosophy characterized by low ego and high execution. In a team setting, I prioritize objective data over personal confirmation, focusing on the seamless delivery of results with pragmatic resilience. As a self-driven problem solver, I thrive on navigating unstructured challenges; I proactively build tools and workflows to bring clarity to ambiguity and ensure project closure. I do not just analyze data points—I strive to uncover the commercial narratives that drive impactful outcomes.
技术与技能栈 Technical Skills & Proficiency
核心分析与金融建模 Core Analytics & Financial Modeling
- 分析工具： Tools: Python (Pandas, Scikit-learn), R (Tidyverse, Tidyquant), SQL
- 方法论： Methodology: 计量经济学建模、回归分析、Brinson 归因模型、PEST/SWOT 分析 Econometric Modeling, Regression Analysis, Brinson Attribution, PEST/SWOT
人工智能与机器学习 AI & Machine Learning
- 算法技术： Techniques: XGBoost / LightGBM, SHAP (可解释性人工智能Explainable AI)
- 自然语言处理： NLP: FinBERT (金融文本/舆情分析NLP/Sentiment Analysis)
业务数字化与协作工具 Operations & Digital Tools
- 精通 Excel/VBA，熟练运用 MS PowerPoint 撰写专业商业策略演示报告，熟练使用 Git/GitHub 进行协作开发与版本管理。 Excel/VBA (Advanced), MS Powerpoint (Professional Strategy Presentation), Git/GitHub
语言能力 Languages
- 英语： English: 专业工作水平 (六级 560+，四级 600+) Professional Working Proficiency (CET-6 560+, CET-4 600+)
- 普通话： Mandarin: 母语 (普通话水平测试二级甲等) Native (PSC Grade 2, Class B)
战略性项目与技术实践 Strategic Projects & Technical Portfolio
海外市场战略调研项目 (国际项目) Overseas Market Strategic Research (Intl. Project)
东风汽车集团 Dongfeng Motor Corp
职责： Role: 带领调研小组，链接海外销售渠道与终端用户，解决“品牌认知低”与“本地化不足”的痛点。 Led a research team to bridge the gap between Chinese tech-advantage and local consumer usage scenarios.
背景： Context: 聚焦豪华新能源汽车品牌的“品牌出海”战略，重点突破中东市场渗透壁垒。 Focused on the 'Brand Going Global' strategy for luxury electric vehicles in the Middle East.
方法： Methodology: 运用 PEST 分析与关税模型，构建涵盖风险评级与消费者用车场景的可视化数据库。 Integrated PEST analysis and quantitative tariff modeling to create a comprehensive 'Market Entry Risk Matrix'.
成果/影响： Impact: 产出《市场进入策略与案例研究报告》，为企业海外市场拓展提供高价值决策依据。 Delivered a decision-support report featuring visualized data and case studies, facilitating strategic localization for the corporate partner.
金融大数据引擎与可解释人工智能风控建模 Financial Data Engine & XAI Risk Modeling
GitHub 开源项目 GitHub Open Source Project
背景： Context: 作为数据分析实验班学生，为了展示自驱力，搭建端到端的金融数据与风控平台。 Developed an end-to-end sandbox platform to demonstrate data engineering and predictive risk modeling.
方法： Methodology: 基于 Python (AKShare) 搭建数据中台；构建 XGBoost 违约预警模型，并利用 SHAP 技术满足金融合规要求；加载 FinBERT 对财经新闻进行舆情分析。 Built a Python data pipeline for tracking metrics; trained an XGBoost model explained via SHAP (Basel compliant); deployed FinBERT for sentiment analysis on news.
成果/影响： Impact: 成功实现数据清洗自动化与风控决策逻辑可视化拆解，量化捕捉市场情绪溢价。 Automated pipeline tracking and successfully integrated auditing-grade explanation dashboards alongside volatility signals.
职场实践与组织经历 Professional Experience & Leadership
校园招聘运营助理 Recruitment Operations Assistant
武汉大学就业指导中心 Wuhan University Career Center
背景： Context: 作为高校与企业间的高效联络桥梁，统筹 21 家头部企业的校招对接。 Managed full-cycle recruitment operations for 21 partner enterprises, bridging university resources with corporate talent needs.
方法： Methodology: 构建基于技能匹配算法的简历初筛工作流，优化招聘各环节对接流程。 Developed an automated screening workflow using skill-matching algorithms to streamline placement and operations.
成果/影响： Impact: 显著提升了企业与学生初试安排的效率与准确度。 Significantly reduced talent identification and scheduling cycle times, improving operational satisfaction.
校园心理健康服务中心 / 数据分析中心 Data Analyst & Growth Lead
武汉大学数据分析中心 WHU Data Analysis & Mental Health Center
背景： Context: 主导校园服务中心新媒体增长与日常数据运维。 Led student services digital strategy and managed core datasets for organizational scaling.
方法： Methodology: 利用 Python 实现经济数据集清洗自动化；基于分析洞察主导社交媒体运营策略。 Automated financial/economic data pipelines for the center and directed data-driven audience engagement initiatives.
成果/影响： Impact: 实现数据清洗自动化（准确率 100%），运营策略调整带来用户基数 19% 的精准增长。 Achieved 100% automation accuracy in pipeline processing and delivered a 19% boost in targeted audience acquisition.